class_docstr: A pretrained model implementation for Grapheme-to-Phoneme (G2P) models
  that take raw natural language text as an input and
  
  Example
  -------
  >>> text = ("English is tough. It can be understood "
  ...         "through thorough thought though")
  >>> from speechbrain.inference.text import GraphemeToPhoneme
  >>> tmpdir = getfixture('tmpdir')
  >>> g2p = GraphemeToPhoneme.from_hparams('path/to/model', savedir=tmpdir) # doctest: +SKIP
  >>> phonemes = g2p.g2p(text) # doctest: +SKIP
docstr: Returns the language for which this model is available
docstr_tok: ["Returns","the","language","for","which","this","model","is","available"]
code: def language(self):
      """Returns the language for which this model is available"""
      return self.hparams.language
  
imports: import torch
  from itertools import chain
  from speechbrain.inference.interfaces import Pretrained, EncodeDecodePipelineMixin
label_desc: Use image node_id 3 for calling the GraphemeToPhoneme obj's underlying member method code with example usage: obj.language() and returns: self